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可扩展人工智能的基础

原文标题 · The Foundations of Scalable AI

一个可扩展的AI系统需要坚实的基础。数据、工程架构、平台、运营模式以及治理体系都必须协同工作才能发挥作用。MIT Technology Review的EmTech Future会议中的这次讨论探讨了在高度监管的环境中构建如此基础架构所需的条件,以及如何通过负责任、可信赖的方式来实现这些功能,从而充分利用包括智能代理在内的新兴技术能力……

来源:MIT Tech Review AI · www.technologyreview.com

正文为英文,可一键机器翻译(仅首次需要等待)

A scalable AI system requires a strong foundation. Data, engineering, platforms, operating models, and governance must converge to work as one. This session from MIT Technology Review’s EmTech Future conference explores what it takes to build that foundation in a highly regulated environment and how a responsible, trustworthy implementation can turn emerging capabilities, including agentic systems, into lasting value for investors.


About the speaker

Jing Wang, Principal, Center for AI and Insights, Vanguard

Jing Wang leads Vanguard’s Center for AI & Insights (CAI), advancing the firm’s AI, machine learning, generative AI, and behavioral science capabilities. Her team drives enterprise-wide innovation, research, and delivery, enabling Vanguard to translate emerging technologies into trusted solutions that enhance client experiences, improve investor outcomes, and create measurable business value.

Before her current position, Jing served in a range of leadership roles across Vanguard’s Financial Services, Workplace Solutions, International, and Corporate Services divisions. Throughout her tenure, she has led teams and enterprise initiatives that advanced strategic priorities, strengthened client outcomes, and drove business performance across the firm.

She joined Vanguard in 2009 after several years as a Principal at the Boston Consulting Group. Jing earned a B.S. in Physics from the University of Science and Technology of China, a Ph.D. from the University of Pennsylvania, and an M.B.A. in Finance and Marketing from the Wharton School of Business at the University of Pennsylvania. Jing holds Series 7, 24, and 65 licenses.